Aug 2026· Management in Education· 0 citations· 23 references
TL;DR
This conceptual paper argues that traditional technology governance models are insufficient and that leaders must develop an augmented moral compass to navigate algorithmic decision-making, data governance, and equity and proposes an original Moral Compass Model.
Abstract
The rapid integration of Artificial Intelligence (AI) into education presents profound ethical challenges that demand a new kind of leadership. This conceptual paper argues that traditional technology governance models are insufficient and that leaders must develop an augmented moral compass to navigate algorithmic decision-making, data governance, and equity. Using a theory synthesis and model-building approach, we draw on scholarship from educational leadership, AI ethics, and critical algorithm studies to propose an original Moral Compass Model. The model rests on six principles—safety, fairness, transparency, privacy, equity, and accessibility—and offers a structured heuristic for moving from reactive policymaking to proactive, value-driven strategy. The paper identifies critical leadership competencies, including ethical stewardship, strategic vision, data-informed deliberation, and collaborative governance, and illustrates them through case vignettes on personalization, assessment integrity, and inclusion. It concludes with a research agenda to empirically test the framework and provides actionable guidelines for policymakers, principals, and superintendents seeking to foster human-centered, ethically governed AI integration in schools. The study contributes to theory by bridging leadership ethics with AI governance and offers a structured lens for future empirical research.
Generative Artificial Intelligence (GenAI) is reconfiguring authority, accountability, and legitimacy in organizational leadership. This mixed-methods study integrates survey data from 542 leaders across health care, finance, government, education, and nonprofits with twenty-two interviews to examine how digital literacy and ethical infrastructure shape trust in AI-mediated decision systems. Findings show that 77% of respondents now incorporate GenAI into leadership decisions, reflecting a shift from hierarchical control to distributed, participatory orchestration. Ethics policies (β = .48, p < .001) and digital literacy (β = .42, p < .001) significantly predict trust in GenAI governance. Interview evidence demonstrates that confidence relies less on technical accuracy than on the institutionalization of ethics, transparent oversight, clear decision rights, bias audits, and mechanisms for contestation and redress. Sectoral contrasts illustrate how power shapes these safeguards, determining who is protected, who bears risk, and who can influence AI-enabled decisions. The study reframes leadership in the algorithmic age as the design of accountable, adaptive, and equitable decision architectures. Leaders who pair ethical governance with digital fluency are best positioned to sustain legitimacy and justice as GenAI becomes embedded in organizational life.
Ajmal Aminee· Organizational Cultures An I...· 0 citations
The framework demonstrates that the sustainable value derived from AI in higher education depends less on the level of the technology adopted than on the ethical bases and consistency of the leadership responsibility for its integration, offering higher education leaders and policymakers a structured path toward responsible AI governance and sustainable institutional transformation.
Asem S. Obied, Ahmed Raja Haj Ali· Frontiers in Education· 0 citations
An academic adaptation of Patrick Rudolf Dannacher's presentation at the 10th Jakarta Geopolitical Forum 2026 is presented, examining Indonesia's strategic position in the evolving global AI landscape.
Patrick Rudolf Dannacher Dannacher· Proceeding Jakarta Geopoliti...· 1 citation
This study examines the transformative impact of artificial intelligence (AI) on the future of work from a human-centered, interdisciplinary perspective, highlighting the necessity of interdisciplinary collaboration to ensure that AI not only enhances efficiency but also promotes justice, well-being, and sustainability.
Cumali Kılıç· Çukurova Üniversitesi Sosyal...· 0 citations
The rapid integration of artificial intelligence (AI) into higher education is transforming how universities are governed, managed, and held accountable. While existing scholarship has focused primarily on the pedagogical applications of AI and the ethical implications of algorithmic technologies, less attention has been devoted to how AI reshapes institutional governance and decision-making processes. Addressing this gap, this paper advances the concept of AI managerialism to explain the growing influence of algorithmic systems on university governance and organizational control.The study employs a critical narrative review and conceptual policy analysis, synthesizing scholarship on AI governance, managerialism, and higher education administration. It further examines three purposively selected cases representing key domains of algorithmic governance: the Ofqual algorithm controversy in the United Kingdom, Purdue University’s Course Signals learning analytics system, and the University of Sydney’s response to generative AI. Through cross-case thematic analysis, the study identifies recurring governance issues related to accountability, transparency, participation, and institutional autonomy.Findings suggest that AI-enabled systems can improve administrative efficiency, predictive capacity, and evidence-informed decision-making while simultaneously generating risks associated with opacity, surveillance, stakeholder exclusion, and the centralization of managerial authority. In response, the paper proposes an Ethical AI Governance Framework for Higher Education built on five principles: mission alignment, transparency and explainability, participatory governance, equity auditing, and bounded scope. Extending existing AI ethics frameworks, the model explicitly incorporates institutional mission, shared governance, and organizational accountability into AI oversight processes. The framework provides practical guidance for university leaders and policymakers seeking to balance technological innovation with academic values and democratic governance. The paper concludes that effective AI governance requires institutionally grounded arrangements that ensure AI supports, rather than undermines, the educational mission of higher education.
Tian-Zi Sun, Mark Joseph D. Pastor· American Journal of Educatio...· 0 citations
The growing integration of artificial intelligence (AI) into organizational management has fundamentally transformed leadership practices. AI challenges traditional leadership paradigms and enables more adaptive, data-driven, and personalized approaches to leading teams and organizations. By leveraging AI, leaders can improve communication and collaboration, anticipate talent needs, analyze real-time data, support leadership development, and address ethical concerns and bias in decision-making. At the same time, AI raises serious concerns about privacy, transparency, job redesign, and the preservation of human qualities such as empathy and moral judgment. Drawing on research in organizational studies, higher and medical education, and library and school leadership, this article examines how AI transforms leadership practices, the resulting challenges, and implications for future leadership development.
Sarwar Khawaja· International Journal of Ser...· 0 citations
